Network Function Virtualization (NFV) has enabled scalable deployment of novel user service requests in current and future communication networks (sixth generation (6G)). However, virtualization also introduces down functioning of certain Key Performance Indicator (KPI)s such as latency. Novel technology like quantum computing has potential to surpass these limitations. One of the problems to tackle in NFV based systems, is decision making for Virtual Network Function (VNF) migration. Classical and quantum solutions are proposed for this problem. It is observed that both solutions ensure anonymity; however lesser overhead is required in the quantum solution. Further, future research directions are discussed as well to inculcate quantum technology into broader class of problems in 6G communication networks.
Network Function Virtualization (NFV) has enabled scalable deployment of novel user service requests in current and future communication networks (sixth generation (6G)). However, virtualization also introduces down functioning of certain Key Performance Indicator (KPI)s such as latency. Novel technology like quantum computing has potential to surpass these limitations. One of the problems to tackle in NFV based systems, is decision making for Virtual Network Function (VNF) migration. Classical and quantum solutions are proposed for this problem. It is observed that both solutions ensure anonymity; however lesser overhead is required in the quantum solution. Further, future research directions are discussed as well to inculcate quantum technology into broader class of problems in 6G communication networks.
This decade has seen an explosion of exploration into softwarisation and virtualization of network functions and services for 6G communication networks and beyond. The concept of service function chaining (SFC) is becoming increasingly integral to proposed solutions that are able to fulfill network requests and services while adhering to the sophisticated key performance indicators (KPIs) of 6G communications and the tactile internet. But new technologies are needed to achieve the set-out cutting-edge requirements and next-generation numbers for low latency, energy efficiency, etc. without suffering from the traditional trade-offs observed when using existing classical technology. Quantum technology is a promising candidate to achieve this, given how it utilizes unique quantum mechanical phenomena like quantum entanglement and quantum interference to resolve problems in a manner often simply non-existent from a classical standpoint. In this paper, we explore utilization of quantum entanglement technology for a specific network scenario involving chains of virtualized network functions (VNFs) that together offer equivalent network functionality, and we discuss some potential advantages of using quantum networks that make use of quantum entanglement over classical technology networks.
Network function virtualization (NFV) is a crucial technology for the 5G network development because it can improve the flexibility of employing hardware and reduce the construction of base stations. There are vast service chains in NFV to meet users’ requests, which are composed of a sequence of network functions. These virtual network functions (VNFs) are implemented in virtual machines by software and virtual environment. How to deploy VMs to process VNFs of the service chains as soon as possible when users’ requests are received is very challenging to solve by traditional algorithms on a large scale. Compared with traditional algorithms, quantum computing has better computational performance because of quantum parallelism. We build an integer linear programming model of the VNF scheduling problem with the objective of minimizing delays, and transfer it into the quadratic unconstrained binary optimization (QUBO) model. Our proposed heuristic algorithm employs a quantum annealer to solve the model. Finally, we evaluate the computational results and explore the feasibility of leveraging quantum computing to solve the VNF scheduling problem.
Quantum computing is a technology that utilizes quantum mechanics principles such as superposition and entanglement to offer significant advantages over classical computing.With the development of sixth generation (6G) technology quantum computing's high data processing capacity, efficiency in optimization processes, and contribution to secure communication systems are becoming increasingly important.This paper examines the role of quantum computing in 6G networks.It discusses its potential contributions in areas such as network optimization, quantum machine learning, secure communication protocols, and fault-tolerant computing.The ultra-low latency, high data rate, and dynamic spectrum management requirements of 6G can be significantly improved by integrating quantum algorithms and hybrid quantum-classical systems.However, obstacles such as current limitations in quantum hardware, error correction requirements, and implementation challenges are also considered in detail.The paper outlines the potential solutions that quantum computing can provide to meet the performance demands of 6G, and discusses future research directions to further explore this promising technology intersection.
In general, quantum technologies and quantum algorithms possess transformative potential for next-generation communication systems. Particularly with the unprecedented data speeds, ultra-low latency, and seamless global connectivity promised by 6G, these technologies are expected to offer significant opportunities for telecommunications and mobile network operators. The integration of quantum computing can play a role in optimizing network operations, improving resource management, reducing energy consumption, and increasing data processing efficiency. For mobile network operators, this will result in significant progress in key performance indicators (KPIs) such as scalability, reliability, and security. Furthermore, quantum cryptography will be of critical importance by introducing new security standards for real-time data protection. This paper will focus on a mobile network operator�s perspective and explore potential solutions. It will assess the synergy between quantum technologies and telecommunications, focusing on key topics such as network latency, bandwidth optimization, and energy efficiency. By leveraging quantum computing, the paper will explore how future telecommunications networks can become faster, more secure, and more sustainable.
The upcoming fifth generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated artificial intelligence (AI) operations. However, fully intelligent network orchestration and management for providing innovative services will only be realized in Beyond 5G (B5G) networks. To this end, we envisage that the sixth generation (6G) of wireless networks will be driven by on-demand self-reconfiguration to ensure a many-fold increase in the network performance and service types. The increasingly stringent performance requirements of emerging networks may finally trigger the deployment of some interesting new technologies, such as large intelligent surfaces, electromagnetic-orbital angular momentum, visible light communications, and cell-free communications, to name a few. Our vision for 6G is a massively connected complex network capable of rapidly responding to the users' service calls through real-time learning of the network state as described by the network edge (e.g., base-station locations and cache contents), air interface (e.g., radio spectrum and propagation channel), and the user-side (e.g., battery-life and locations). The multi-state, multi-dimensional nature of the network state, requiring the real-time knowledge, can be viewed as a quantum uncertainty problem. In this regard, the emerging paradigms of machine learning (ML), quantum computing (QC), and quantum ML (QML) and their synergies with communication networks can be considered as core 6G enablers. Considering these potentials, starting with the 5G target services and enabling technologies, we provide a comprehensive review of the related state of the art in the domains of ML (including deep learning), QC, and QML and identify their potential benefits, issues, and use cases for their applications in the B5G networks. Subsequently, we propose a novel QC-assisted and QML-based framework for 6G communication networks while articulating its challenges and potential enabling technologies at the network infrastructure, network edge, air interface, and user end. Finally, some promising future research directions for the quantum- and QML-assisted B5G networks are identified and discussed.
Abstract Sixth Generation (6G) communication networks are anticipated to advance the fifth generation technologies as well as introduce new revolutionary technologies to deliver aggressive data rates, end-to-end latency, reliability, energy efficiency, security, network capacity, and mobility requirements of the future innovative applications. To deliver these demands, ultra-fast and secure computing capability for processing a huge amount of data, application-related tasks, and resource management algorithms will be required. Many 6G applications will use advanced learning techniques that work on large data sets and their working can be made more efficient with the help of Quantum Computing (QC) instead of conventional classical computing. In this paper, we provide an overview of QC and 6G networks and highlight the benefit of integrating these two technologies. We briefly review the recent work and present a framework for QC-assisted 6G networks. We also discuss four use cases of QC in 6G networks, including quick task offloading, fast optimization algorithm results, efficient machine learning techniques, and improved security. Finally, we discuss several open challenges of using QC in the context of 6G network applications.